1. Field of the Invention
The invention relates generally to the field of digital imaging and computer graphics. More specifically, the invention relates to methods for performing digital image processing and compression.
2. Description of the Related Art
In small, portable devices such as digital still cameras, image compression schemes should be suited to reduce the storage requirements and processing time of captured sensor images still maintaining acceptable picture quality even after compression and decompression. When storage requirements and processing time are reduced, the overall power consumption of the device is also reduced since the VLSI (Very Large Scale Integration) chip performing the processing is more compact. The reduction of the bit rate for transmission or storage of still image and motion video will also speed the process of capturing images and thus, speed the downloading of them to a PC (personal computer) or other more complex data processing systems. Quick capture and compression of an image will allow such cameras to transition to the next image, i.e., to the next click of the camera speedily.
Image compression, whether performed by hardware such as VLSI chip or by software, can be classified as either "lossy" or "lossless". With lossless compression, the original image prior to compression can be retrieved exactly when the compressed image is decompressed. Consequently, lossless techniques, whose compression ratios depend greatly upon the entropy of an image, do not achieve high compression ratios and, since they preserve a high percentage of original image information, are computationally expensive. By contrast, lossy compression provides only an approximation of the original image. Thus, with lossy compression, greater compression ratios can be achieved but traditionally with lower image quality compared to lossless techniques. One such lossy technique, referred to as "predictive coding" (also called Digital Pulse Code Modulation (DPCM), well-known in the art), predicts the value of a successive pixel by linearly combining the properties of already processed neighboring pixels. An error pixel is defined as the difference between the original image pixel and the corresponding predicted pixel. The error pixel, represented as a color value, is quantized and then binary encoded. Traditionally, the quantization has been performed distinct from the encoding, which lends to complexity in the processing circuitry.
Even with lossy compression schemes, the process of quantization and encoding is often very compute intensive. Thus, it would be desirable to reduce or eliminate the computing of quantization and encoding within a small device such as a digital camera. Doing so would reduce the circuitry or chip area required and also, the power consumption.
With lossy techniques, as traditionally employed, image quality suffers. It would also be desirable in situations where captured image quality is important, such as a digital camera, to employ a compression scheme that is "visually-lossless". A "visually-lossless" scheme would technically be lossy, but due to certain properties would model the human visual system. To the naked eye, images compressed using a "visually-lossless" scheme would appear approximately identical to the original image.
The implementation of such computationally intensive techniques demands more VLSI circuitry than is suitable for digital cameras and portable, small devices desiring image compression. Thus, there is a need for a more efficient process to perform techniques while conserving power. Also, there is a need to preserve image quality as it relates to the human visual system such that a lossy image appears to the unaided eye as "lossless".